Sift Science

Puntos a favor

Workflows functionality (is like the main actions an user can perform while inside our services platform) and Rules functionality (inside each Workflow one can set high number of options and criteria to execute actions (Blocking, Reviewing, etc.) these two features bring what we need in order to map fraudsters and behaviors alike, while at the same time they Machine Learning engine learns from us! Making everything we create inside the tools a lesson learn and then we can focus on the other kind of attacks, relying on the tool.

Puntos en contra

The reporting is so basic it contrast with the high functionality and advanced Machine Learning tool it needs to be improved. Here is where tools like Ravelin excel Sift Science by far!.

Puntos a favor

I like that it helps me find suspicious interactions between users. It does get me if a user has a network of accounts and if they are the same person by verifying if they are using the same device.

Puntos en contra

It is a bit tricky to use. There are so many options and so much to discover it can be a little bit overwhelming. But once you know what you're doing (kinda) you should be all set.

Puntos a favor

The scores we receive on transactions are usually quite accurate and fast, and they have helped us avoid many potentially fraudulent orders.

Puntos en contra

We have had some issues where we are unable to locate a transaction in the system to further investigate, even though we received a score for the order.